Multistatic human micro-Doppler classification of armed/unarmed personnel

Classification of different human activities using multistatic micro-Doppler data and features is considered in this paper, focusing on the distinction between unarmed and potentially armed personnel. A database of real radar data with more than 550 recordings from 7 different human subjects has been collected in a series of experiments in the field with a multistatic radar system. Four key features were extracted from the micro-Doppler signature after Short Time Fourier Transform analysis. The resulting feature vectors were then used as individual, pairs, triplets, and all together before inputting to different types of classifiers based on the discriminant analysis method. The performance of different classifiers and different feature combinations is discussed aiming at identifying the most appropriate features for the unarmed vs armed personnel classification, as well as the benefit of combining multistatic data rather than using monostatic data only

Personnel recognition based on multistatic micro-Doppler and singular value decomposition features

The use of micro-Doppler signatures experimentally collected by a multistatic radar system to recognise and classify different people walking is discussed. A suitable feature based on singular value decomposition of the spectrograms is proposed and tested with different types of classifiers. It is shown that high accuracy of between 97 and 99% can be achieved when multistatic data are used to perform the classification

Experimental analysis of multistatic multiband radar signatures of wind turbines

This study presents the analysis of recent experimental data acquired using two radar systems at S-band and X-band to measure simultaneous monostatic and bistatic signatures of operational wind turbines near Shrivenham, UK. Bistatic and multistatic radars are a potential approach to mitigate the adverse effects of wind farm clutter on the performance of radar systems, which is a well-known problem for air traffic control and air defence radar. This analysis compares the simultaneous monostatic and bistatic micro-Doppler signatures of two operational turbines and investigates the key differences at bistatic angles up to 23°. The variations of the signature with different polarisations, namely vertical transmitted and vertical received and horizontal transmitted and horizontal received, are also discussed

Multistatic Radar: System Requirements and Experimental Validation

Multistatic radar provides many advantages over conventional monostatic radar, such as enhanced information on target signatures and improvements in detection which are due to the multiple perspectives and differences in the properties of clutter. Furthermore, the fact that receive-only multistatic nodes are passive may be an advantage in military applications. In order to quantify potential performance benefits of these advantages a comprehensive understanding of target and clutter behaviour in multistatic scenarios is necessary. However, such information is currently limited because bistatic and multistatic measurements are difficult to make, their results depend on many variables such as multistatic geometry, frequency, polarization, and many others, and results from previous measurements are likely to be classified for military targets. Multistatic measurements of targets and clutter have been performed over the past few years by the NetRAD system developed at the University College London and the University of Cape Town. A new system, NeXtRAD, is now being developed in order to investigate some of the many aspects of multistatic radar. This paper discusses the results obtained with the previous system and the lessons learnt from its use. These points are then discussed in the context of the new radar, defining key important factors that have to be considered when developing a new multistatic radar system

Measurements of multistatic X&L band radar signatures of UAVs

This paper illustrates the results of a series of measurements of multistatic radar signatures of small UAVs at L and X band. The system employed was the multistatic multiband radar system, NeXtRAD, consisting of one monostatic transmitter-receiver and two bistatic receivers. Results demonstrate the capability of the system of recording bistatic data with baselines and two-way bistatic range of the order of few kilometres

Measurements of the Multistatic X&L Band Radar Signatures of UAVS

This paper illustrates the results of a series of measurements of multistatic radar signatures of small UAVs at L and X band. The system employed was the multistatic multiband radar system, NeXtRAD, consisting of one monostatic transmitter-receiver and two bistatic receivers. Results demonstrate the capability of the system of recording bistatic data with baselines and two-way bistatic range of the order of few kilometres

Measurements and discrimination of drones and birds with a multi‐frequency multistatic radar system

This article presents the results of a series of measurements of multistatic radar signatures of small UAVs at L‐ and X‐bands. The system employed was the multistatic multiband radar system, NeXtRAD, consisting of one monostatic transmitter‐receiver and two bistatic receivers. NeXtRAD is capable of recording simultaneous bistatic and monostatic data with baselines and two‐way bistatic range of the order of a few kilometres. The paper presents an empirical analysis with range‐time plots and micro‐Doppler signatures of UAVs and birds of opportunity recorded at several hundred metres of distance. A quantitative analysis of the overall signal‐to‐noise ratio is presented along with a comparison between the power of the signal scattered from the drone body and blades. A simple study with empirically obtained features and four supervised‐learning classifiers for binary drone versus non‐drone separation is also presented. The results are encouraging with classification accuracy consistently above 90% using very simple features and classification algorithms

First Measurements with NeXtRAD, a Polarimetric X/L Band Radar Network

NeXtRAD is a fully polarimetric, X/L Band radar network. It is a development of the older NetRAD system and builds on the experience gained with extensive deployments of NetRAD for sea clutter and target measurements. In this paper we will report on the first measurements with NeXtRAD, looking primarily at sea clutter and some targets, as well as early attempts at calibration using corner reflectors, and an assessment of the polarimetric response of the system. We also highlight innovations allowing for efficient data manipulation post measurement campaigns, as well as the plans for the coming years with this system

Fusion of Deep Representations in Multistatic Radar Networks to Counteract the Presence of Synthetic Jamming

Micro-Doppler signatures are extremely valuable in the classification of a wide range of targets. This work investigates the effects of jamming on micro-Doppler classification performance and explores a potential deep topology enabling low bandwidth data fusion between nodes in a multistatic radar network. The topology is based on an array of three independent deep neural networks (DNNs) functioning cooperatively to achieve joint classification. In addition to this, a further DNN is trained to detect the presence of jamming and from this it attempts to remedy the degradation effects in the data fusion process. This is applied to real experimental data gathered with the multistatic radar system NetRAD, of a human operating with seven combinations of holding a rifle-like object and a heavy backpack which is slung on their shoulders. The resilience of the proposed network is tested by applying synthetic jamming signals into specific radar nodes and observing the networks’ ability to respond to these undesired effects. The results of this are compared with a traditional voting system topology, serving as a convenient baseline for this work

Potential of Double-crested Cormorants (\u3ci\u3ePhalacrocorax auritus\u3c/i\u3e), American White Pelicans (\u3ci\u3ePelecanus erythrorhynchos\u3c/i\u3e), and Wood Storks (\u3ci\u3eMycteria americana\u3c/i\u3e) to Transmit a Hypervirulent Strain of \u3ci\u3eAeromonas hydrophila\u3c/i\u3e between Channel Catfish Culture Ponds

Aeromonas hydrophila is a Gramnegative bacterium ubiquitous to freshwater and brackish aquatic environments that can cause disease in fish, humans, reptiles, and birds. Recent severe outbreaks of disease in commercial channel catfish (Ictalurus punctatus) aquaculture ponds have been associated with a hypervirulent Aeromonas hydrophila strain (VAH) that is genetically distinct from less virulent strains. The epidemiology of this disease has not been determined. Given that research has shown that Great Egrets (Ardea alba) can shed viable hypervirulent A. hydrophila after consuming diseased fish, we hypothesized that Doublecrested Cormorants (Phalacrocorax auritus), American White Pelicans (Pelecanus erythrorhynchos), and Wood Storks (Mycteria americana) could also serve as a reservoir for VAH and spread the pathogen during predation of fish in uninfected catfish ponds. All three species, when fed VAH-infected catfish, shed viable VAH in their feces, demonstrating their potential to spread VAH